Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_846264_weight_decay_0.02.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021450398489832878
Inter Cos: 0.11371058225631714
Norm Quadratic Average: 27.691619873046875
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023355256766080856
Inter Cos: 0.07800136506557465
Norm Quadratic Average: 33.90126419067383
Nearest Class Center Accuracy: 0.34275

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03040088713169098
Inter Cos: 0.08377153426408768
Norm Quadratic Average: 25.405349731445312
Nearest Class Center Accuracy: 0.3745

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02630358748137951
Inter Cos: 0.06745846569538116
Norm Quadratic Average: 26.443557739257812
Nearest Class Center Accuracy: 0.4105

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.037549808621406555
Inter Cos: 0.08572380244731903
Norm Quadratic Average: 16.906005859375
Nearest Class Center Accuracy: 0.435875

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03619251400232315
Inter Cos: 0.07008745521306992
Norm Quadratic Average: 17.17981719970703
Nearest Class Center Accuracy: 0.4995

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06030216068029404
Inter Cos: 0.08328840136528015
Norm Quadratic Average: 10.59411334991455
Nearest Class Center Accuracy: 0.745

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.1822052150964737
Inter Cos: 0.11650187522172928
Norm Quadratic Average: 7.029384613037109
Nearest Class Center Accuracy: 0.99975

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 38.80926513671875
Linear Weight Rank: 4031
Intra Cos: 0.6374971866607666
Inter Cos: 0.22308902442455292
Norm Quadratic Average: 57.28459167480469
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 15.738786697387695
Linear Weight Rank: 3670
Intra Cos: 0.8942197561264038
Inter Cos: 0.2877826988697052
Norm Quadratic Average: 29.016521453857422
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.6828252077102661
Linear Weight Rank: 10
Intra Cos: 0.941901683807373
Inter Cos: 0.32484638690948486
Norm Quadratic Average: 18.46148681640625
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9581224322319031
Inter Cos: 0.44318509101867676
Norm Quadratic Average: 11.878942489624023
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.3746733779907228
Accuracy: 0.6075
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.20348937809467316, Weights: 0.018769852817058563
NC2 Equiangle: Features: 0.3654407925075955, Weights: 0.1397029028998481
NC3 Self-Duality: 0.3408597707748413
NC4 NCC Mismatch: 0.12849999999999995

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480457365512848
Inter Cos: 0.09352367371320724
Norm Quadratic Average: 27.530664443969727
Nearest Class Center Accuracy: 0.2895

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02309596911072731
Inter Cos: 0.07319683581590652
Norm Quadratic Average: 33.811824798583984
Nearest Class Center Accuracy: 0.358

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030099106952548027
Inter Cos: 0.08179215341806412
Norm Quadratic Average: 25.334671020507812
Nearest Class Center Accuracy: 0.4045

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025302696973085403
Inter Cos: 0.06167759373784065
Norm Quadratic Average: 26.391033172607422
Nearest Class Center Accuracy: 0.443

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.034201838076114655
Inter Cos: 0.0862162634730339
Norm Quadratic Average: 16.87276840209961
Nearest Class Center Accuracy: 0.456

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03080526925623417
Inter Cos: 0.06493250280618668
Norm Quadratic Average: 17.13197898864746
Nearest Class Center Accuracy: 0.4885

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.037753790616989136
Inter Cos: 0.07660666853189468
Norm Quadratic Average: 10.545559883117676
Nearest Class Center Accuracy: 0.548

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.055676307529211044
Inter Cos: 0.10465070605278015
Norm Quadratic Average: 6.848264694213867
Nearest Class Center Accuracy: 0.6325

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 38.80926513671875
Linear Weight Rank: 4031
Intra Cos: 0.15238289535045624
Inter Cos: 0.21697339415550232
Norm Quadratic Average: 50.30299758911133
Nearest Class Center Accuracy: 0.6145

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 15.738786697387695
Linear Weight Rank: 3670
Intra Cos: 0.24121712148189545
Inter Cos: 0.33256426453590393
Norm Quadratic Average: 23.889726638793945
Nearest Class Center Accuracy: 0.5985

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.6828252077102661
Linear Weight Rank: 10
Intra Cos: 0.2542991638183594
Inter Cos: 0.37636813521385193
Norm Quadratic Average: 15.097902297973633
Nearest Class Center Accuracy: 0.592

Output Layer:
Intra Cos: 0.25401151180267334
Inter Cos: 0.4123242199420929
Norm Quadratic Average: 9.642048835754395
Nearest Class Center Accuracy: 0.579

